code: def get_data():
      with open("train.json", "r") as raw_data:
          data = json.load(raw_data)
  
      df = pd.DataFrame(data)
      target = df.pop("interest_level").apply(encode)
  
      df = FeatureEngineer().fit_transform(df)
      return df, target
  
file_path: mlcourse.ai/jupyter_russian/topic06_features/demo.py
imports: import numpy
  import pandas
  import json
  from sklearn.base import TransformerMixin
label_desc: Use image node_id 2 for calling a global function with example usage: get_data() and returns: df,  target